code: def test_script(self, input_param, input_shape, expected_shape):
      # test whether support torchscript
      net = FeaturePyramidNetwork(**input_param)
      data = OrderedDict()
      data["feat0"] = torch.rand(input_shape[0])
      data["feat1"] = torch.rand(input_shape[1])
      test_script_save(net, data)
  
file_path: MONAI/tests/test_fpn_block.py
imports: from __future__ import annotations
  import unittest
  from collections import OrderedDict
  import torch
  from parameterized import parameterized
  from monai.networks.blocks.backbone_fpn_utils import _resnet_fpn_extractor
  from monai.networks.blocks.feature_pyramid_network import FeaturePyramidNetwork
  from monai.networks.nets.resnet import resnet50
  from monai.utils import optional_import
  from tests.utils import SkipIfBeforePyTorchVersion, test_script_save
label_desc: Use image node_id 2 for calling the TestFPNBlock obj's underlying member method code with example usage: obj.test_script(input_param, input_shape, expected_shape) without return types